We study the choice between source-based and destination-based corporate taxes in a two-country model, allowing multinational firms to use transfer pricing to allocate profits across tax jurisdictions. We show that source-based taxation is a Nash equilibrium for tax revenue maximizing...

This paper provides new insights into a key element of the global corporate tax reform agenda: the choice between a source-based and a destination-based corporate tax system. We study the government choice between source-based and destination-based taxes in a two-country model, allowing...

We study the choice between source-based and destination-based corporate taxes in a two-country model, allowing multinational firms to use transfer pricing to allocate profits across tax jurisdictions. We show that source-based taxation is a Nash equilibrium for tax revenue maximizing...

We propose a new “global” market share indicator that complements the traditional export market share analysis by accounting for the foreign value added embodied in the production process and for the performance of national firms on their domestic market. We also consider all the income from...

Firms adjust to differences in market size and demand uncertainty by changing the frequency and size of their export shipments. In our inventory model, transportation costs and optimal shipment frequency are determined on the basis of demand as well as inventory and per shipments costs. Using a...

This paper analyzes how firms adjust to differences in market size and demand uncertainty by changing the frequency and size of their export shipments. In our inventory model, transportation costs and optimal shipment frequency are determined on the basis of demand as well as inventory and per...

This paper provides evidence that learning about demand is an important driver of firms' dynamics. We present a simple model with Bayesian learning in which firms are uncertain about their idiosyncratic demand parameter in each of the markets they serve, and update their beliefs as noisy...